@inproceedings{fec7c5b703174d4cbfa4cf3fad085c65,
title = "Generating artificial images by generative adversary network",
abstract = "This paper presents a case study of the structure, generative adversary network (GAN). The primary goal of this project is to apply the concept of GAN (Generative Adversary Network) to generate a group of artificial images with same theme, which are expected to give a realistic view to human eyes in final stage. This independent research mainly focuses on basic structure of GAN and the improvement of its quality via implementing a variation, DCGAN. Thus, it can offer solid foundations and help to our team to focus on exploring a possibility of this fair new technology.",
keywords = "DCGAN, Deep convolution, GAN, Generative adversary nets, MNIST, TensorFlow",
author = "Yunhao Zhang and Yanxin Zhou and Huang, {Ching yu}",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 2019 International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2019 ; Conference date: 26-08-2019 Through 28-08-2019",
year = "2019",
month = aug,
day = "26",
doi = "10.1145/3357777.3357794",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "52--55",
booktitle = "PRAI 2019 - Proceedings of 2019 International Conference on Pattern Recognition and Artificial Intelligence",
}